Abstract

In spite of the growing literature about adult attention-deficit
hyperactivity disorder (ADHD), relatively little is known about the prevalence
and correlates of this disorder.

Aims

To estimate the prevalence of adult ADHD and to identify its demographic
correlates using meta-regression analysis.

Method

We used the MEDLINE, PsycLit and EMBASE databases as well as hand-searching
to find relevant publications.

Results

The pooled prevalence of adult ADHD was 2.5% (95% CI 2.1–3.1). Gender
and mean age, interacting with each other, were significantly related to
prevalence of ADHD. Meta-regression analysis indicated that the proportion of
participants with ADHD decreased with age when men and women were equally
represented in the sample.

Conclusions

Prevalence of ADHD in adults declines with age in the general population.
We think, however, that the unclear validity of DSM–IV diagnostic
criteria for this condition can lead to reduced prevalence rates by
underestimation of the prevalence of adult ADHD.

Although attention-deficit hyperactivity disorder (ADHD) has long been
thought to be a disabling and common disorder that occurs only in childhood,
more recent research, including prospective longitudinal follow-up studies,
suggests that ADHD persists into adulthood in a high proportion of
cases.1–8
Adult ADHD studies indicate a high degree of genetic
predisposition,9,10
and reveal structural and functional brain
abnormalities11–14
congruent with neuropsychological
data.14–16
Attention-deficit hyperactivity disorder is a serious risk factor for comorbid
psychiatric disorders (antisocial personality disorder, substance misuse and
affective
disorders),17,18
and also shows significant correlation with poor socio-economic outcome and
functional impairment (lower level of education, higher level of unemployment,
and higher rates of unsuccessful marriages, criminality and road traffic
accidents).1,7,8,18–23

In spite of the growing literature dealing with adult ADHD, relatively
little is known about the prevalence of the disorder among adults and its
correlates. To our knowledge no meta-analysis of the epidemiological data on
adult ADHD has been published. The aim of our study was to estimate the
prevalence of ADHD in adulthood using a meta-regression approach and to
identify demographic factors that might influence the prevalence of ADHD in a
given population.

Method

Study selection

We searched MEDLINE, PsycLit and EMBASE for publications dealing with the
epidemiology of adult ADHD. Only publications in English were considered. As a
first step, we created four databases with the keywords ADULT, ADHD,
EPIDEMIOLOGY and PREVALENCE respectively. Second, we connected the ADULT and
ADHD databases with a logical `and' operation, generating a new database
containing only those publications that were part of both ADULT and ADHD
databases in the first step. The other two databases (EPIDEMIOLOGY and
PREVALENCE) were connected with the `or' operation, creating a new database
including all publications that were originally in the EPIDEMIOLOGY and
PREVALENCE databases. During the final step, the two new databases were
connected with the `and' operation. In addition to this search procedure, we
used the reference lists of the identified publications to find further
relevant articles. After excluding follow-up and family studies–which do
not provide prevalence data for adult ADHD–and studies that dealt with
the prevalence of ADHD in special groups (people with panic or bipolar
disorder, drug addiction or obesity, or people in prison), 12 population-based
studies remained:

one study estimated the cumulative incidence of ADHD at the age of 19 years
based on retrospective
analysis;24

one study estimated the prevalence of adult ADHD among licensed
drivers;25

three studies estimated the prevalence of ADHD among university
students;26–28

one study estimated the prevalence of ADHD among a non-clinical sample from
an out-patient psychiatric
service;29

six studies provided a community-based estimate: oppositional defiant
disorder only and ADHD only v. oppositional defiant disorder + ADHD
in clinic and community adult
samples;30 a
cross-national
survey;31 the
National Comorbidity Survey
Replication;32 the
Mexican National Comorbidity
Survey;33 a
telephone survey;34
and the Nijmegen Health Area Study
2.19

For our meta-regression analyses six studies were omitted. Three of these
studies (Kessler et
al,32
Medina-Mora et
al33 and
Fayyad et
al31) were not
included because they did not provide raw data for the prevalence and
demographic variables necessary for the computations. The study by Barbaresi
et al24
was not included because it dealt only with the cumulative incidence of ADHD
between the ages of 5 and 19 years and accordingly provided information about
ADHD in adolescents rather than in adults. The study by Weyandt et
al26 was not
included because it measured only the prevalence of attention-deficit symptoms
and not the prevalence of adult ADHD. Finally, we omitted the study by Gadow
et al30
because these authors did not use
DSM–IV35
criteria for the diagnosis of adult ADHD. The modified diagnostic criteria
used by Gadow et al did not include age at onset or functional
impairment criteria, and applied a threshold of five rather than six
symptoms.30
Lowering the diagnostic threshold concerning symptom counts has a dramatic
effect on prevalence estimates; inclusion of data based on a lower symptoms
threshold would therefore have introduced substantial heterogeneity in the
meta-analysis.

Variables

For the purpose of the meta-analysis we extracted the following domains or
variables from the articles that were finally included:

data describing the study–date of publication, country, number of
arms;

data describing the target population–sample size, mean age, age
range, standard deviation for age range, gender composition (proportion of
males in the sample);

diagnostic tools for adult ADHD–self-report, structured
interview;

results–prevalence rate according to DSM–IV criteria (total and
subtypes if provided), prevalence rate according to alternative criteria, if
available (total and subtypes, if given).

Statistical analysis

A mixed-effect (with fixed and random effects) meta-regression–a
meta-analytic technique of multivariate linear regression across
studies–was applied to estimate the prevalence of ADHD across various
study samples and in order to evaluate the impact of potential demographic
variables of interest including age and gender on the prevalence estimates.
The meta-regression analysis that we adopted in this investigation was based
on van Houwelingen et al's general linear mixed-model technique based
on the approximate likelihood
approach.36 In
particular, the log-odds of the observed prevalence in each study were
regressed using intercept and basic study-level demographic covariates that
included average age and gender composition from each of the individual
studies. Interaction between the two covariates (age, gender composition) was
also included in the model. In addition, a random-effect intercept term
representing systematic between-study variation (heterogeneity) was also
incorporated in the meta-regression model. A common weighted prevalence
estimate for ADHD was calculated as a DerSimonian & Laird estimator, based
on the random effects component of the mixed model that incorporated both
fixed and random
effects.37

Results

Study design

In all the articles included in the analysis we found that although the
sample sizes were large (typically several hundreds of participants), the
authors collected samples of convenience, which do not assure
representativeness. Accordingly, the raw estimates of prevalence from these
studies cannot be extended to the general population. We note that in the
study by Faraone &
Biederman,34 raw
prevalence estimates were weighted by US census data (based on age, ethnicity,
education, geographic region and number of telephone lines within the
household) in order to derive prevalence estimates generalisable for the
population; however, the final derived prevalence estimates remain
questionable in light of the high refusal rate (approximately 80%) in the
target population that was used to derive the prevalence estimates in the
sampling phase of the study. In the study by DuPaul et al,in addition
to the problem with representativeness, there were remarkable differences
across the three subsamples in terms of the number, gender and age range of
the participants (Tables 1 and
2).27

Age

In most of the studies, the sample's mean age was low compared with the
mean age of a typical adult population. Specifically, although the mean ages
were 19.4–44.9 years for all samples in the analysis (the mean age,
weighted by the number of participants in each study, was 34 years), for the
majority of samples the mean age ranged between 19.4 and 28.5 years. Only one
study had a mean age of 44.9
years,19 whereas
two studies had a mean age of around 35
years.25,34
(Of these two studies, Faraone & Biederman provided estimates for mean age
based on weighting using the US census
data;34Table 1).

Gender

With the exception of one study sample (the USA arm of the study by DuPaul
et al),27
the gender proportions were neither balanced nor representative of the target
population. There were extreme differences in the male: female ratio across
the groups in the study by DuPaul et
al,27 with a
substantial departure from the population gender distribution in two arms of
this study, possibly as a result of the above-mentioned convenience sampling
(Table 1).

Diagnosis

The studies included in our meta-analysis applied different methodology and
design with regard to sampling and diagnosing adults with ADHD
(Table 2). All studies employed
DSM–IV diagnostic criteria, even though all–except for Faraone & Biederman34
and Almeida Montes et
al29–questioned
the validity of DSM–IV criteria for ADHD when applied to
adults.35 In terms
of association between symptoms that underlie the DSM–IV diagnosis of
adult ADHD and functional impairment (used as an external validator of the
disorder), Kooij et al found the strongest association from four
symptoms being present (as opposed to the threshold of six symptoms according
to the DSM–IV diagnostic
system).19 DuPaul
et al27
and Heiligenstein et
al28 applied
alternative diagnostic criteria with a lower threshold, besides the original
DSM–IV criteria. Although Murphy & Barkley used only DSM–IV
diagnostic criteria in their study, they suggested the possibility of
modifying these criteria for adult ADHD in
future.25 Faraone & Biederman considered two types of diagnoses for adult ADHD: a `broad'
diagnosis for screening purposes, which followed the DSM–IV criteria but
was more inclusive concerning symptom severity; and a `narrow' diagnosis based
solely on DSM–IV
criteria.34

Estimated prevalence and correlates of adult ADHD

Mixed-effect meta-regression analysis was applied to estimate the
prevalence across samples and to investigate prevalence as a function of
gender composition and mean age in the respective samples. Results of the
meta-regression analysis indicated that the pooled prevalence of ADHD across
samples was 2.5% (95% CI 2.1–3.1; t=42.3, P<0.0001)
(Fig. 1).

Adopting the likelihood approach as recommended by Hardy &
Thompson36 and van
Houwelingen,38
heterogeneity among studies included in the meta-analysis was tested by the
likelihood ratio statistic, by comparing the maximum log-likelihood (LL) of
the random-effect model with that of the fixed-effect model. Our results
showed that the random and fixed-effects models yielded maximum LL values
of–9.9 and–42.5 respectively. This indicates a statistically
significant heterogeneity across studies (χ2=65.2, d.f.=1,
P<0.0001), which (as shown by subsequent analyses) was due, at
least in part, to the principal demographic variables that we examined in our
study. In particular, our results showed that the prevalence of ADHD was
significantly related to the gender composition in the sample
(t=4.34, P=0.012, standardised beta for log-odds of observed
prevalence 15.19 × 10–2) and to the mean age
(t=3.03, P=0.039, standardised beta for log-odds of observed
prevalence 20.98 × 10–2). Furthermore, the interaction
between the two covariates also reached statistical significance
(t=–3.42, P=0.027, standardised beta for log-odds of
observed prevalence 0.50 × 10–2). The association
between the proportion of participants with ADHD and gender composition and
mean age is shown in Fig. 2.
Owing to the statistically significant interaction reported above, for
illustrative purposes the association of prevalence with gender composition is
displayed at various ages (20, 30 and 40 years;
Fig. 2(a)); for younger age
groups the prevalence increases, whereas for the older age group prevalence
decreases with higher proportion of males in the sample. Analogously, for
illustrative purposes the association of prevalence with mean age was broken
down by male percentage of the sample (a third, a half, two-thirds;
Fig. 2(b)); the prevalence
decreases with age when men are represented at 50% or more in the sample, but
increases with age when women are predominantly represented in the sample
(male proportion, 33.3%).

Relationship between gender composition (% male) and prevalence (%) of
adult attention-deficit hyperactivity disorder (ADHD). Meta-regression
analysis indicated that gender and mean age, interacting with each other, were
statistically significantly related to the prevalence of ADHD in the sample.
(a) Relationship between gender composition and prevalence at ages 20, 30 and
40 years. (b) Relationship between age and prevalence as a function of gender
composition (a third, a half, two-thirds males).

We note that the above results are based on prevalence data that relied on
DSM–IV diagnostic criteria. Individual studies included in our
meta-analysis used other diagnostic criteria as well, but these alternative
criteria varied between studies, precluding a meaningful pooling of the
results. Indeed, as Table 3
shows, these alternative thresholds lead to substantial variation in the
results (prevalence between 2.5% and 42.3%), reflecting the heterogeneity of
the alternative diagnostic approaches in the individual studies.

Discussion

In general, epidemiological data about adult ADHD have been collected from
three different sources: family studies, follow-up studies and
population-based studies. In family studies, parents of children who did not
have ADHD–who had taken part in case–control ADHD studies as the
control group–were examined for adult ADHD. The results of these studies
cannot be generalised since they used a strongly selected sample, excluding a
genetically predisposed group–parents of children with
ADHD.34

Follow-up studies are long-term prospective studies designed to determine
the persistence of ADHD among adolescents and adults by following an index
ADHD group of school-aged children and a matched control group. Follow-up
studies show that ADHD persists in 4–66% of the cases into
adulthood.1–8
Such variability in the persistence of the disorder into adulthood can be
explained–at least in part–by methodological differences such as
small sample sizes; non-representative, predominantly clinical samples;
different diagnostic criteria among and across studies; and changing the
source of information during the follow-up from parent report to self-report
only. These methodological differences imply that follow-up studies are
difficult to compare and the results of those studies can neither be
generalised nor used for estimating prevalence of ADHD in adulthood.

Population-based studies estimated prevalence rates of adult ADHD at
1–7.3% applying DSM–IV
criteria.19,24,25,27–29,31–35
Most of these studies were designed for direct estimation of the prevalence of
adult ADHD in a target population such as a community, university students,
prisoners or a special population of patients. These studies typically used a
large sample and therefore were usually appropriate for estimating prevalence
with sufficient precision. However, they did not assure representativeness,
since they were based on a sample of convenience. In general, the mean age of
the participants was low compared with a typical adult population, and there
were several studies in which the gender proportion of the sample was
significantly unbalanced. In addition, the diagnostic tools and the approach
for the identification of cases usually varied from study to study.

Gadow et al provided estimates of the prevalence of adult ADHD
using a large, representative sample of the general
population.30
Nevertheless, because these authors applied only modified diagnostic criteria,
their prevalence data are difficult to compare with the prevalence estimates
from other studies that relied on the original DSM–IV classification.
Two studies, being parts of large-scale epidemiological surveys–the
National Comorbidity
Survey39 and the
World Health Organization (WHO) World Mental Health
Surveys40–did
not provide crude estimates for the prevalence of adult ADHD in their sample;
they used indirect estimation in order to assess the prevalence of adult ADHD
in the general population. The first of these studies (Kessler et
al32) examined
an US sample, whereas the second (Fayyad et
al31)
estimated cross-national prevalence in ten countries. We note that despite
these two studies applying the same general approach, the first estimated
prevalence at
4.4%,32 whereas the
second estimated the prevalence in the US sample at
5.2%.31 Based on
the authors' comments, this discrepancy is attributable to the fact that
certain predictors for the prevalence estimation that were used in the first
(USA only) study were not available in the second (multinational) study. In
the second study, the prevalence estimates of adult ADHD across samples showed
a substantial variation: they were between 1.2% and 7.3%, with an estimated
general cross-national prevalence of
3.4%.31 In both
studies, prevalence estimates were based on multiple imputation using a
combination of directly interviewed cases and multiply imputed cases from the
remainder of the sample. In all cases (directly interviewed and multiply
imputed) in both samples the individuals were aged 18–44 years;
prevalence estimates for higher age ranges were based on weighting
data.31,32
The aforementioned indirect estimations (applied in both studies) of the
prevalence of adult ADHD in the general population hinge on prediction
equations that were obtained in a relatively small sample (n=154). It
is not clear how reliably these equations can predict the occurrence of ADHD,
and what the exact predictors are. With regard to the multinational study, it
must be noted that the prediction equation of the US sample was extrapolated
to other countries, a potential limitation pointed out by the authors. A third
study, conducted as part of the WHO survey, estimated the 12-month prevalence
of ADHD in
Mexico;33 however,
like the parent study it did not provide a crude prevalence estimate for the
targeted sample and therefore was not included in our meta-analysis.

In summary, published estimates of the prevalence of adult ADHD vary
greatly.19,25,27–29,31–34
After reviewing the pertinent publications, we attributed this variability to
methodological and diagnostic differences between the studies. In addition,
only self-reports were used as a source of information and in some studies
there was a lack of information about the relevant childhood symptoms that
would be necessary for the proper diagnosis of adult
ADHD.26–28

Correlation of prevalence with gender and age

Our finding of a pooled prevalence rate for adult ADHD of 2.5% (95% CI
2.1–3.1) seems to be conservative in the context of the research
discussed above. Our pooled prevalence estimates were derived from studies
that provided data for crude prevalence based on strict DSM–IV criteria
for diagnosing ADHD. In two of these studies, however, indirect estimates were
derived by assessing ADHD symptoms in childhood and asking only a single
question about the persistence of problems with ADHD into
adulthood.31,32

Polanczyk et al recently estimated the worldwide prevalence of
ADHD in a meta-regression analysis of 102 articles regarding child and
adolescent ADHD.41
Although the pooled prevalence of ADHD in children and adolescents according
to these authors was 5.29%, they also reported that the prevalence in
adolescents was around
3%.41 This estimate
is consistent with our pooled prevalence data, especially in light of the
finding about the relationship between age and prevalence of ADHD.

A growing number of studies indicate that biased samples might underlie
extreme gender effects on the prevalence of ADHD in clinically referred
paediatric study samples. Specifically, some of these studies suggest that a
weaker association with conduct disorder and disruptive behaviour in girls
compared with boys might result in lower numbers of female
referrals.42–44
In contrast to the clinical samples, in which male: female ratios as high as
10: 1 have been
observed,45,46
community samples showed a less extreme gender ratio (male: female risk 3: 1)
in the prevalence of ADHD in
childhood.43,44
Compared with paediatric and adolescent studies, adult ADHD studies have
generally shown a more balanced distribution of prevalence in men and women.
This may be attributable to the fact that whereas childhood referrals are
usually initiated by parents or teachers, in adulthood self-referrals are
common. The observation that women with ADHD have more internalising problems
than men, which leads to a higher rate of self-referrals in
adulthood,47 may
underlie the more balanced gender ratio in adult samples.

In the studies that were included in our analysis, samples were
community-based and the authors found heterogeneous gender ratios but no
significant gender effect on prevalence in their samples when applying
DSM–IV diagnostic
criteria.19,25,27–29,34
In two studies that were not included in our meta-analysis owing to the lack
of crude prevalence
data,31,32
the authors found modest gender effects on prevalence, with a significantly
higher proportion of men in their ADHD group. In spite of the findings of the
studied articles that supported no significant gender effect on prevalence,
using the raw data of the individual studies we identified gender as another
factor that has an impact on the prevalence of adult ADHD. In this case –
as in the case of effect of age – we presume that methodological
differences and questions concerning sample selection and case identification
underlie the absence of or modest appearance of gender effects in
community-based samples.

Our findings indicate that the prevalence of adult ADHD has a significant
negative association with age, although this association is moderated by the
gender composition of the sample. The explanation and the potential practical
use of this finding are complex. Specifically, available literature and
clinical experience indicate a modulation of the presentation of symptoms of
ADHD by
adulthood.48–50
Conceptualisation of ADHD as a developmental disorder entails that, although
the disabling feature of the disorder remains, both the quality and the
severity of symptoms may change over time. Thus, applying the diagnostic
criteria created for children may not be appropriate in adulthood. The
developmental nature of the disorder also means that although new cases do not
emerge in adulthood, there might be a certain number of children who `outgrow'
the disorder. This concept predicts reduced prevalence in adulthood because of
the nature of the disorder. In view of our finding of a significant
age–gender interaction, this concept might be mainly true for male ADHD
cases with more hyperactive symptoms and linked disruptive behavioural
problems than female ADHD cases in general.

Several studies reported that symptoms of ADHD declined with
age.25,28,31,32,34,51
At the same time, functional impairment and low socio-economic outcome can be
detected even with a reduced number of
symptoms19,23,31,41,48
These observations lead us to another possible conclusion, that some children
with ADHD do not outgrow the disorder but `outgrow the diagnostic
criteria',1 meaning
that reduced prevalence among adults results from an underestimation of the
true prevalence of adult ADHD. Our finding that prevalence increases with age
when women are predominantly represented in the sample might relate to the
previously mentioned possibility of `pseudo-new' cases of ADHD, when women
with this disorder who were not referred for treatment in childhood owing to
the absence of disruptive behavioural problems refer themselves in adulthood
because of emerging comorbid psychiatric disease.

Two other factors concerning the diagnosis of adult ADHD should be
mentioned, since either of them may result in underestimation of the
prevalence of the disorder. First, based on the finding of the Milwaukee
study,1 –
relevant also to clinical experience – it seems that the source of
information might have a great impact on diagnosing ADHD: the persistence of
ADHD was five to nine times higher when based on parent's report than when
based on self-report, and parent's reports also showed higher potential to
predict functional impairment than did
self-report.1 The
second factor is the problem of symptom recall. Several authors pointed out
that collecting data with retrospective self-report would underestimate the
prevalence of adult ADHD, since adults do not remember their childhood
symptoms properly. Empirical findings are inconsistent concerning this
issue.1,52–60
In the Milwaukee follow-up study, at the adult follow-up only 47% of the
participants recalled having ADHD in childhood from the original ADHD index
group.1 Their
self-report showed only 20% concordance with their parents' report concerning
their childhood
symptoms.1 Manuzza
et al on the other hand, in the results of the New York follow-up
study, reported good symptom recall (the sensitivity of retrospective
diagnosis of ADHD was 0.78 and the specificity was 0.89) based on self-reports
in the index group at the adult
follow-up.52 These
authors noted that this might result from the fact that participants in the
index group were from a clinically referred sample. Moreover, they suggested
that adults who were not hospitalised in their childhood might have had poorer
symptom recall.52
The fact that in the New York study there was a high rate of false positive
cases in the control group, according to Manuzza et
al,52 raises
the possibility of problematic symptom recall among people who do not have
ADHD.

In summary, we think that our finding is consistent with the suggestion
that the prevalence of ADHD declines with age; however, the background of this
phenomenon remains unclear and a caveat is needed in this regard.
Specifically, the validity of DSM–IV diagnostic criteria for diagnosing
adult ADHD is an important issue, emerging both from the interpretation of our
findings and also from the relevant literature. It seems that diagnosing adult
ADHD on the basis of strict DSM–IV criteria – as well as the
above-mentioned methodological difficulties – may lead to
underestimation of the prevalence of the disorder in this age group. Thus,
further investigations are necessary to find out in what proportion
methodological questions or natural developmental features are responsible for
the observed decline in the prevalence of ADHD with age. Future well-designed,
community-based epidemiological studies critically depend on an improved
understanding of the aetiology and pathophysiology of the disorder, which in
turn would help to improve the current diagnostic criteria and would thereby
facilitate more reliable identification of people with ADHD. We must note that
the small number of studies included in the meta-regression analysis and the
above-detailed methodological difficulties of the reviewed and analysed
studies are also potential limitations of our findings.